I use the svm function (for regression) to make forecast like I would with for exemple the arima function:
fit<-auto.arima(ts)
prediction<-forecast(fit,h=20)
which returns different attributes :
prediction$mean
which is the actual predictionprediction$lower
andprediction$upper
which are the boundaries of the confidence intervals on each points of theprediction$mean
.
I would like the svm
function (from e1071 package) to return a more detailed answer than just the value (like the forecast()
would).
But I guess it is not implemented in the function yet.
Is there another function to do it ? Or should I use bootstrap methods to try to estimate those boundaries? And if I should use this are they pre-implemented version of them instead of using sample over a for loop which is very time-consuming ?